Data Engineer

· Design, develop, test, deploy, and maintain batch and near-real-time ETL/ELT pipelines for structured and semi-structured data.

· Build and orchestrate ingestion and transformation workflows using Azure Data Factory and Azure Databricks.

· Develop scalable data models, transformations, stored procedures, and performance-optimized workloads in Snowflake.

· Use PySpark, Python, and SQL to cleanse, integrate, validate, and transform data across cloud and enterprise sources.

· Implement monitoring, logging, alerting, retry, and error-handling mechanisms to improve pipeline reliability.

· Apply data-quality checks, reconciliation controls, lineage, documentation, security, and access-control standards.

· Collaborate with architects, analysts, application teams, and business stakeholders to translate requirements into data solutions.

· Participate in code reviews, CI/CD deployments, production support, root-cause analysis, and continuous optimization.

· We are seeking a Data Engineer with 3-5 years of experience to design, build, and support scalable data pipelines and cloud-based analytics solutions. The role requires hands-on expertise in ETL/ELT, Snowflake, Azure Data Factory, and Azure Databricks, with a strong focus on data quality, performance, reliability, and secure delivery., · Bachelor degree in Computer Science, Information Technology, Engineering, or a related field.

· 3-5 years of hands-on experience in data engineering, data integration, or cloud data-platform development.

· Strong experience designing ETL/ELT pipelines and working with dimensional/data-warehouse concepts.

· Hands-on proficiency with Snowflake, including data loading, transformations, query tuning, and warehouse optimization.

· Practical experience with Azure Data Factory for linked services, datasets, pipelines, triggers, and orchestration.

· Practical experience with Azure Databricks, Apache Spark/PySpark, notebooks, clusters, and Delta Lake concepts.

· Strong SQL skills and working proficiency in Python; experience integrating relational, file, API, and cloud-storage sources.

· Understanding of Git-based version control, CI/CD, Agile delivery, and secure cloud data practices.

· Strong analytical, troubleshooting, communication, and documentation skills.

PREFERRED SKILLS

· Azure Data Lake Storage Gen2, Delta Lake, Azure DevOps, Git, REST APIs, data governance/lineage, Snowpipe, dbt, and Microsoft Azure or Snowflake certifications.